Leaky-Wave-Enabled Horn Antenna Exhibiting Customizable Contour and Wideband Radiation Characteristics for Millimeter-Wave Applications
Bibliographic record
Abstract
Conventional horns inevitably suffer from the phase error issue and associated design constraint of contour (e.g., the optimum criteria are typically employed) because of the embedded plane-to-cylindrical (or spherical) wavefront conversion process. These design dilemmas can be well addressed by using the leaky-wave enabled horn (i.e., the leaky horn), which mainly exploits the intrinsic plane-wavefront characteristics of leaky waveguides’ wedge-shaped regions. While noticing that previously reported leaky horns are subject to a narrowband nature and somewhat limited contour designability, a leaky horn class exhibiting wideband and customizable contour characteristics, which are based on a leaky grounded coplanar waveguide (GCPW), are developed in this communication. After establishing the theoretical relationship between the aperture length, flaring angle, and leakage constant of a general leaky horn and revealing several relevant design considerations, design technicalities and procedures for simultaneously realizing customizable contour and wideband radiation are systematically described for the GCPW leaky horn. For demonstration, a GCPW leaky horn example using the slow-wave technique is constructed, simulated, and measured. It is verified that the proposed GCPW leaky horn has several merits like customizable contour, wide bandwidth, suppressed phase error, compact size, etc., which enable it to be a potential candidate for millimeter-wave applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".